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Scientific Machine Learning Jobs in Arizona (NOW HIRING)

Insight Enterprises

Principal Data Scientist

Phoenix, AZ · On-site

$150 - $210/hr

We are seeking a Principal Data Scientist with deep clinical or healthcare and life sciences ... Design machine learning workflows using Azure Machine Learning, including experimentation, model ...

Intel

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$103K - $142K/yr

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

Deloitte

Senior AI Engineer - SFL Scientific

Tempe, AZ

$100K - $137K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

University of Arizona

Scientific Analyst II

Tucson, AZ · On-site

Data Analysis and Machine Learning Pipeline Development: * Under moderate guidance collaborate in ... Scientific Communication, Dissemination, and Collaboration: * Compare and contribute to peer ...

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex ... Requirements: * Bachelor's degree required in Mathematics, Data Science, Computer Science ...

Staffingine LLC

AIML Engineer

Scottsdale, AZ · On-site

Experience implementing and supporting endtoend Machine Learning workflows and patterns * Expert level programming skills in Python and experience with Data Science and ML packages and frameworks

Honeywell International, Inc.

Lead AI Engineer

Phoenix, AZ · On-site

$96K - $126K/yr

... scientific machine learning, and surrogate modeling at major conferences and journals. About us: Join a company that's reintroducing itself to the aviation community we've helped advance for more ...

Intel

Senior AI / Data Science Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

Lead development of advanced AI, Machine Learning, and Generative AI solutions that address ... Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics. Performing yield ...

Unitek Learning

People Data Scientist

Tempe, AZ · On-site

The People Data Scientist applies advanced statistical, analytical, and data science methodologies ... This role leverages predictive modeling, experimentation, machine learning, and workforce analytics ...

Unitek Learning

People Data Scientist

Tempe, AZ · On-site

The People Data Scientist applies advanced statistical, analytical, and data science methodologies ... This role leverages predictive modeling, experimentation, machine learning, and workforce analytics ...

Unitek Learning

People Data Scientist

Tempe, AZ

The People Data Scientist applies advanced statistical, analytical, and data science methodologies ... This role leverages predictive modeling, experimentation, machine learning, and workforce analytics ...

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Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Arizona?

For Scientific Machine Learning jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Arizona look for?

The top searched job categories for Scientific Machine Learning jobs in Arizona are:

What cities in Arizona are hiring for Scientific Machine Learning jobs?

Cities in Arizona with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 2% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer I

Rocket Lab Corporation

Tucson, AZ

$115K - $152K/yr

Full-time

Posted 3 days ago

New

Rocket Lab rating

9.2

Company rating: 9.2 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

4th of 72 rated aerospace companies

Job description

ABOUT ROCKET LAB

Rocket Lab is the end-to-end space company building rockets, spacecraft, and critical subsystems that keep the world connected, protected, expand humanity's reach to the Moon, Mars, and beyond. We move fast, build real hardware for meaningful missions, and make the impossible routine. Come shape the future with us.

SPACE SYSTEMS

At Rocket Lab, we're not just launching rockets — we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more.

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space — our world class Space Systems team is empowering some of the boldest and most ambitious space missions.

SENIOR MACHINE LEARNING ENGINEER I

Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Senior Machine Learning Engineer I based at our Optical Systems sites in Tucson, AZ, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.

WHAT YOU'LL DO

  • Contribute your experience to developing solutions for real-world problems.
  • Design, train, and deploy machine learning models for Optical Systems applications
  • Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
  • Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
  • Preform rapid prototyping and enhanced development to be integrated into operational systems.
  • Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
  • Stay current with ML research and evaluate new tools, frameworks, and techniques

WHAT WE'RE LOOKING FOR IN A SENIOR MACHINE LEARNING ENGINEER I:

  • Bachelor's degree and 5+ years of experience, master's degree and 3+ years of experience, or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
  • Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
  • Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
  • Strong math background, particularly linear algebra
  • Proficiency in Python
  • Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
  • Software engineering fundamentals: version control, testing, CI/CD, containerization
  • S. citizenship is required, due to program requirements
  • Ability to obtain and maintain an U.S. Government Security Clearance

NICE TO HAVE:

  • Proficiency in C/C++/Rust
  • Experience curating quality, real-world datasets for training deep learning models
  • TS/SCI security clearance

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

WHAT TO EXPECT

We're on a mission to unlock the potential of space to improve life on Earth, but that's not an easy task. It takes hard work, determination, relentless innovation, teamwork, grit, and an unwavering commitment to achieving what others often deem impossible. Our people out-think, out-work, and out-pace. We pride ourselves on having each other's backs, checking our egos at the door, and rolling up our sleeves on all tasks big and small. We thrive under pressure, work to tight deadlines, and our focus is always on how we can deliver, rather than dwelling on the challenges that stand in the way.

Important information:

FOR CANDIDATES SEEKING TO WORK IN US OFFICES ONLY:

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), Rocket Lab Employees must be a U.S. citizen, lawful U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be eligible to obtain the required authorizations from the U.S. Department of State and/or the U.S. Department of Commerce, as applicable. Learn more about ITAR here.

Rocket Lab provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment at Rocket Lab, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Applicants requiring a reasonable accommodation for the application/interview process for a job in the United States should contact Giulia Johnson at g.biow@rocketlabusa.com.This dedicated resource is intended solely to assist job seekers with disabilities whose disability prevents them from being able to apply/interview. Only messages left for this purpose will be considered. A response to your request may take up to two business days.

FOR CANDIDATES SEEKING TO WORK IN NEW ZEALAND OFFICES ONLY:

For security reasons, background checks will be undertaken prior to any employment offers being made to an applicant. These checks will include nationality checks as it is a requirement of this position that you be eligible to access equipment and data regulated by the United States' International Traffic in Arms Regulations.

Under these Regulations, you may be ineligible for this role if you do not hold citizenship of Australia, Japan, New Zealand, Switzerland, the European Union, or a country that is part of NATO, or if you hold ineligible dual citizenship or nationality. For more information on these Regulations, click here ITAR Regulations.

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